IT environments generally encompass many objects that are related to each other in some manner. These objects may correspond to both physical entities such as computers and virtual entities such as databases. Managing the objects and their relationships to each other is critical to the smooth operation of any IT environment.
Conventional IT management practices are subject to a number of problems that are common to a wide variety of IT environments. For example, most IT management systems have some store of IT objects that the IT department is responsible for. This store may be a flat file, a simple comma-separated-value (CSV) file, a database, a configuration management database (CMDB), an asset management system, or a combination thereof. These stores typically contain data that represents everything in the IT environment. This may include a vast amount of data that can be overwhelming to users, and may make it difficult for users to focus the data that is relevant to their everyday tasks, or to specific problems that may involve only a small subset of the IT environment.
Some systems provide means to visualize or extract information from the data that is in the data store. Fewer systems allow relationships between specific objects within the IT environment to be defined. Those systems that do allow relationships to be defined typically include all of the available data and consequently result in a huge graph of objects. Again, the large amount of information that is presented to the user may be overwhelming, and consequently of little value to the user.
Some systems attempt to provide higher-level features around such graphs. For example, some products provide mechanisms to traverse the graphs graphically. Others use the data in the graph to attempt to perform root cause analysis, impact analysis, dependency analysis, or other types of analysis of the data. Because these features are based on the entirety of the available data, however, it may be difficult for the user to identify the portion of the data or the corresponding analysis that is meaningful. In other words, the user may not be able to identify the meaningful information in the midst of the “noise” of the meaningless information.
This problem may in turn cause the value of the data in the data store to degrade. Because many of the objects in the data store are simply not relevant to most administrators most of the time, there may be no meaningful way to partition responsibility for these objects. As a result, no particular administrator may have an interest in updating these objects, and their information may become out-of-date. Further, when devices go out of service, administrators frequently fail to update the data store, and instead simply ignore that object if it shows up in results derived from the store. Administrators may in some instances have to remember knowledge about the states of objects because there is no means to record this knowledge in the data store. In a relatively short period of time, the data in the store age, becomes out-of-date and untrustworthy, and effectively serve no purpose other than to obscure other, meaningful data.
It would therefore be desirable to provide a mechanism that encourages users, including administrative staff, stakeholders and end users who own, administer, manage and rely on IT objects to maintain data in the data store in a cost effective manner.